Power Query queries can be refreshed manually or by taking advantage of scheduled refresh capabilities in specific products (such as Power BI) or even programmatically (by using the Excel object model).
Power Query offers the ability to work against a subset of the entire dataset to define the required data transformations, allowing you to easily filter down and transform your data to a manageable size.
Volume (data sizes), velocity (rate of change), and variety (breadth of data sources and data shapes) In the event that you need to modify the process or query to account for underlying data or schema changes, you can use the same interactive and intuitive experience you used when you initially defined the query. When using Power Query to access and transform data, you define a repeatable process (query) that can be easily refreshed in the future to get up-to-date data. Highly interactive and intuitive experience for rapidly and iteratively building queries over any data source, of any size.Īny shaping is one-off and not repeatable Power Query enables connectivity to a wide range of data sources, including data of all sizes and shapes.Įxperiences for data connectivity are too fragmentedĬonsistency of experience, and parity of query capabilities over all data sources.ĭata often needs to be reshaped before consumption Existing challengeįinding and connecting to data is too difficult Several challenges contribute to this situation, and Power Query helps address many of them. How Power Query helps with data acquisitionīusiness users spend up to 80 percent of their time on data preparation, which delays the work of analysis and decision-making.
Diagram with symbolized data sources on the right, passing though Power query for transformation, and then going to various destinations, such as Azure Data Lake Storage, Dataverse, Microsoft Excel, or Power BI.
0 kommentar(er)
